The manufacturing of semiconductor devices is based on sophisticated process technologies such as optical lithography to define semiconductor structures in the submicrometer regime. Optical lithography projects light through a patterned mask to transfer the pattern into a light sensitive resist on a semiconductor substrate. It is immediately evident that any deviations of the actual mask pattern from a target mask layout deteriorate the accuracy of the lithography process. For this reason significant efforts have been put in improving mask fabrication.
Masks for optical lithography are typically fabricated using beam lithography, such as electron beam writing or laser beam writing. Beam lithography involves exposing a radiation sensitive resist on a mask substrate by beam writing. The resist is then developed to remove the exposed (in the case of a positive tone resist) or unexposed (in the case of a negative tone resist) resist portions. The resist portions that remain are used as a basis for a pattern transfer on the mask substrate. This pattern transfer step may include, for example, etching in the opened areas of the patterned resist a masking layer underneath the resist. After resist removal, the remaining, non-etched portions of the masking layer define the mask pattern.
It has been found that the pattern of the etched masking layer after resist removal often deviates from the target mask layout. There are various reasons for such deviations, including artefacts introduced by a beam-writing tool (e.g., beam blur and focus errors), physical effects of beam writing (e.g., electron scattering) and process artefacts (e.g., resist blur, process loading effects of one or both of development and etching, and pattern transfer effects).
Electron scattering correction is well established in electron beam lithography. When a resist has been exposed by electron beam writing, electron scattering prevents that the developed resist regions mirror exactly the exposed resist regions. Electron scattering occurs within the resist itself as well as at the underlying mask substrate (in terms of backscattering). As one result of electron scattering, edges of mask features in close proximity to other mask features are moved after development compared to their intended positions and compared to isolated mask features (this effect is called proximity effect). Moreover, some of the scattered electrons escape the resist towards the beam-writing tool and are reflected back by an objective lens of the tool (this effect is called fogging). Correction of backscattering, proximity effect and fogging are widely employed today to compensate electron scattering artefacts.
A further correction technique called Optical Lithography Correction (OPC) targets at compensating distortions accumulated during the overall manufacturing process of semiconductor devices. OPC corrects such distortions by moving feature edges or by adding/removing feature areas to the pattern on the lithography mask. To this end, OPC predicts the optical lithography and is calibrated using experimental data from the actual manufacturing process. Since the manufacturing process is based on a particular lithography mask, any mask imperfections also enter the OPC model via the experimental data and will thus be corrected. On the downside, OPC modeling “freezes” the mask fabrication process and cannot distinguish between distortions caused by mask fabrication on the one hand and distortions from optical lithography on the other.
In view of the various shortcomings of OPC modeling, attempts to individually model distortions caused by mask fabrication have been made. Most mask process correction attempts are based on empirical models using convolution kernels and rule-based processing. However, it was found that the empirical models often fail in case of complex mask layouts. Moreover, since the models are not based on the physics and chemistry of mask fabrication, the validity of a particular model is limited to a particular dataset defining a particular mask layout.
Attempts to consider the physics and chemistry of mask fabrication mimic and correct artefacts resulting from resist development and pattern transfer. As an example, various etch models have been proposed to correct pattern transfer artefacts. Such etch models consider density-dependent etch rates and open area-dependent etch rates.
Nonetheless, certain feature configurations such as inverse line ends or contacts can still not sufficiently be modeled taking into account these etch rate effects. On the other hand, the complexity of resist chemistry and of the physics underlying the etching step (e.g., in case of plasma etching) currently prohibit a fully exhaustive modeling of the mask fabrication process due to the computational power required for modeling the process within the given time constraints.